• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.161-168
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• 2009

The ubiquitous transportation system environments make it possible to collect each vehicle's position and velocity data and to perform more sophisticated traffic flow management at individual vehicle or platoon level through V2V and V2I communication. It is necessary to develop a new traffic management paradigm to take advantage of the ubiquitous transportation system environments. This paper proposed a preventive congestion management algorithm for uninterrupted flow, whose goal is to minimize the incident potential and maximize the productivity by maintaining traffic flow stability. The algorithm includes the following steps: Processing the raw data to produce the 3-dimension speed/flow/density profile and to produce the platoon profile and the shock wave profile, Determining the traffic state and the flow stability based on the processed data, Deciding the desirable speed the according the traffic flow state, and finally Providing the desirable speed information. It remains as further work to perform field experiments and calibrate the algorithm parameters.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.69-82
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• 2002

The objective of this study is to evaluate the performance of macroscopic traffic flow models with the analytical and field data. Five candidate models were selected as follows ; Lax Method Model, Upwind Scheme Model, Hilliges'Model, Papageorgiou's Model, and Cell-Transmission Model. In the analytical test scenario, the traffic condition was assumed that could cause the building and dissipation of queue, and each model was compared with analytical solutions and the numerical results. An analytical test indicated that both simple continuum and high order continuum models are able to reproduce queue building and dissipating behavior in a reasonable way A field test has shown that Upwind and Papageorgiou's model show similar performances. Considering the simplicity in model formulation and numerical computation, we firstly recommend Upwind scheme model , and secondly Papageorgiou's model that performed will to represent traffic flow in tests as candidate models for further development of simulation model for Naebu expressway in Seoul.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.125-135
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• 2004

The validity of simulation has been well-established for decades in areas such as computer and communication system. Recently, the technique has become entrenched in specific areas such as transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and their driver's characteristics, even though it is known that they are important factors for any traffic flow analysis, have never been considered sufficiently. In this paper, the traffic simulation using a multi-agent approach with considering vehicle dynamics is proposed. The multi-agent system is constructed with the traffic environment and the agents of vehicle and driver. The traffic environment consists of multi-lane roads, nodes, virtual lanes, and signals. To ensure the fast calculation, the agents are performed on the based of the rules to regulate their behaviors. The communication frameworks are proposed for the agents to share the information of vehicles' velocity and position. The model of a driver agent which controls a vehicle agent is described in the companion paper. The vehicle model contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation has proceeded for an interrupted and uninterrupted flow model. The result has shown that the driver agent performs human-like behavior ranging from slow and careful to fast and aggressive driving behavior, and that the change of the traffic state is closely related with the distance and the signal delay between intersections. The system developed shows the effectiveness and the practical usefulness of the traffic simulation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.86-99
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• 2021

One of the methods to alleviate traffic congestion is to increase the efficiency of the roads by providing traffic condition information on road user and distributing the traffic. For this, reliability must be guaranteed, and quantitative real-time traffic speed prediction is essential. In this study, and based on analysis of traffic speed related to traffic conditions, historical data correlated with traffic flow were used as input. We developed an LSTM model that predicts speed in response to normal traffic conditions, along with a CNN-LSTM model that predicts speed in response to incidents. Through these models, we try to predict traffic speeds during the hour in five-minute intervals. As a result, predictions had an average error rate of 7.43km/h for normal traffic flows, and an error rate of 7.66km/h for traffic incident flows when there was an incident.

• International Journal of Highway Engineering
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• v.18 no.5
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• pp.117-125
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• 2016

PURPOSES : The density in uninterrupted traffic flow facilities plays an important role in representing the current status of traffic flow. For example, the density is used for the primary measures of effectiveness in the capacity analysis for freeway facilities. Therefore, the estimation of density has been a long and tough task for traffic engineers for a long time. This study was initiated to evaluate the performance of density values that were estimated using VDS data and two traditional methods, including a method using traffic flow theory and another method using occupancy by comparing the density values estimated using vehicular trajectory data generated from a radar detector. METHODS : In this study, a radar detector which can generate very accurate vehicular trajectory within the range of 250 m on the Joongbu expressway near to Dongseoul tollgate, where two VDS were already installed. The first task was to estimate densities using different data and methods. Thus, the density values were estimated using two traditional methods and the VDS data on the Joongbu expressway. The density values were compared with those estimated using the vehicular trajectory data in order to evaluate the quality of density estimation. Then, the relationship between the space mean speed and density were drawn using two sets of densities and speeds based on the VDS data and one set of those using the radar detector data. CONCLUSIONS : As a result, the three sets of density showed minor differences when the density values were under 20 vehicles per km per lane. However, as the density values become greater than 20 vehicles per km per lane, the three methods showed a significant difference among on another. The density using the vehicular trajectory data showed the lowest values in general. Based on the in-depth study, it was found out that the space mean speed plays a critical role in the calculation of density. The speed estimated from the VDS data was higher than that from the radar detector. In order to validate the difference in the speed data, the traffic flow models using the relationships between the space mean speed and the density were carefully examined in this study. Conclusively, the traffic flow models generated using the radar data seems to be more realistic.

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.115-131
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• 2001

The Purpose of this study is to develop a simulation model for large-scale network with interrupted flow as well as uninterrupted flow. The Cell Transmission(CT) theory is used to simulate traffic flow. Flow transition rules have been newly developed to simulate traffic flows at merging and diverging sections, and signalized intersections. In the model, it is assumed that dynamic OD table is exogenously given. Simulation results for toy network shows that the model can explain queue dynamics not only in signalized intersections of urban arterials, but also in merging and diverging sections of freeway. In case study, the model successfully simulated traffic flows of 145,000 vehicles on CBD network of city of Seoul with 74 traffic zones, 133 signalized intersections among 395 nodes and 1110 links.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.4
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• pp.1-11
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• 2014

Traffic congestion cost is more likely to occur in the inner city than interregional road, and it accounts for about 63.39% of the whole. Therefore, it is important to mitigate traffic congestion of the inner city. Traffic congestion in the urban could be divided into Recurrent congestion and Non-recurrent congestion. Quick and accurate detection of Non-recurrent congestion is also important in order to relieve traffic congestion. The existing studies about incident detection have been variously conducted, however it was limited to Uninterrupted Traffic Flow Facilities such as freeway. Moreover study of incident detection on the interrupted Traffic Flow Facilities is still inadequate due to complex geometric structure such as traffic signals and intersections. Therefore, in this study, incident detection model was constructed using by Artificial Neural Network to aim at urban arterial road that is interrupted traffic flow facility. In the result of the reliability assessment, the detection rate were 46.15% and false alarm rate were 25.00%. These results have a meaning as a result of the initial study aimed at interrupted traffic flow. Furthermore, it demonstrates the possibility that Non-recurrent congestion can be detected by using car navigation data such as car navigator system device.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4D
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• pp.527-538
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• 2011

Currently, the only established criteria is on the location of bus stops on principal roads where uninterrupted flow mainly occurs. There are no clear guidelines on any method to locating bus stops considering the characteristics of bus operation and pedestrians. If the location or exterior of a bus stop is inappropriate, road users including bus drivers and pedestrians will be caused serious dangerous and inconvenience. In this study, the research below was performed in order to propose rational criteria for the location of bus stops integrated with or separated from speed-change lanes at signalized intersections considering smooth traffic flow and the characteristics of bus operation and pedestrians as well as traffic safety : First, the appropriate length of each of the near-side and far-side bus stops was calculated by categorizing bus stops to be constructed into those integrated with speed-change lanes and those separated from speed-change lanes. Secondly, the appropriate length of each of the bus stops divided into near-side bus stops and far-side bus stops and integrated with or separated from speed-change lanes was selected by considering the characteristics of pedestrians. Thirdly, whether the construction locations of bus stops were appropriate or not was determined based on the appropriate length of bus stops integrated with or separated from speed-change lanes, which was calculated and selected by considering traffic flow and the characteristics of pedestrians and considering traffic safety. The method for locating bus stops considering traffic flow, the characteristics of pedestrians, and traffic safety will be able to help suggestion criteria of bus stop and the location of safe and pleasant bus stops.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.2
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• pp.13-23
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• 2016

Many traffic centers are highly hesitant in employing existing Automatic Incident Detection Algorithms due to high false alarm rate, low detection rate, and enormous effort taken in maintaining algorithm parameters, together with complex algorithm structure and filtering/smoothing process. Concerns grow over the situation particularly in Freeway Incident Management Area This study proposes a new algorithm and introduces a novel concept, the Displaced Flow Index (DiFI) which is similar to a product of relative speed and relative occupancy for every execution period. The algorithm structure is very simple, also easy to understand with minimum parameters, and could use raw data without any additional pre-processing. To evaluate the performance of the DiFI algorithm, validation test on the algorithm has been conducted using detector data taken from Naebu Expressway in Seoul and following transferability tests with Gyeongbu Expressway detector data. Performance test has utilized many indices such as DR, FAR, MTTD (Mean Time To Detect), CR (Classification Rate), CI (Composite Index) and PI (Performance Index). It was found that the DR is up to 100%, the MTTD is a little over 1.0 minutes, and the FAR is as low as 2.99%. This newly designed algorithm seems promising and outperformed SAO and most popular AIDAs such as APID and DELOS, and showed the best performance in every category.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.107-116
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• 2005

The information on travel time in providing the information of traffic to drivers is one of the most important data to control a traffic congestion efficiently. Especially, this information is the major element of route choice of drivers, and based on the premise that it has the high degree of confidence in real situation. This study developed a vehicle arrival time prediction algorithm called as "VAT-DV" for 6 corridors in total 6.1Km of "Nam-san area trffic information system" in order to give an information of congestion to drivers using VMS, ARS, and WEB. The spatial scope of this study is 2.5km~3km sections of each corridor, but there are various situations of traffic flow in a short period because they have signalized intersections in a departure point and an arrival point of each corridor, so they have almost characteristics of interrupted and uninterrupted traffic flow. The algorithm uses the information on a demand volume and a queue length. The demand volume is estimated from density of each points based on the Greenburg model, and the queue length is from the density and speed of each point. In order to settle the variation of the unit time, the result of this algorithm is strategically regulated by importing the AVI(Automatic Vehicle Identification), one of the number plate matching methods. In this study, the AVI travel time information is composed by Hybrid Model in order to use it as the basic parameter to make one travel time in a day using ILD to classify the characteristics of the traffic flow along the queue length. According to the result of this study, in congestion situation, this algorithm has about more than 84% degree of accuracy. Specially, the result of providing the information of "Nam-san area traffic information system" shows that 72.6% of drivers are available.